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Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques

Continuous Variables and Their Probability Distributions
Continuous Variables and Their Probability Distributions

Exploring Data Using Base SAS Software
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... Dispersion refers to the spread of the data values, usually with respect to a particular measure of central tendency. Some measures of dispersion are the range, the variance, the standard deviation, the coefficient of variation, and the Interquartlle range, Range is the difference between the smalle ...
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...  The probability of any event is between 0 and 1.  All possible outcomes together must have probabilities whose sum is 1.  If all outcomes in the sample space are equally likely, the probability that event A occurs can be found using the formula ...
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... Step 2: Label each axis with the type of information it contains. Step 3: Decide what scale to use (how much each line represents), based on the range of data you want to show; e.g., if you had data with a range from 0-80 cm, you might choose an increase of 10 cm for each line. Step 4: Draw marks to ...
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... 1. This formula avoids the separate calculations of the means, standard deviations, and the deviations from the means. 2. This formula is easier and more accurate: minimizes round-off error. ...
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Relationships between Alpha Coefficient and Scale Stability Index

Since we are dealing with count data, seems reasonable to fit this
Since we are dealing with count data, seems reasonable to fit this

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... 3. Problem 5 from the text Explain why the formulas for sample variance and population variance are different. The extreme scores in a population that is approximately normal in shape are less likely to be included in a sample because of their rarity. Thus, the sample is usually less variable than t ...
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... sources with the variation among individuals who should be similar. In particular, ANOVA tests whether several populations have the same mean by comparing how far apart the sample means are with how much variation there is within the sample. ...
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Probability and Probability Distributions Probability Concepts

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Notes for Chapter 2 of DeGroot and Schervish Conditional

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pdf preprint file

... Multivariate Analysis Needs ... Nonparametrics! ...
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History of statistics

The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, ""statistics"" means both sets of collected information, as in national accounts and temperature records, and analytical work which requires statistical inference.Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.A number of statistical concepts have had an important impact on a wide range of sciences. These include the design of experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.
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